From f391ac176392a9df7120ade387e74eb3e729daf9 Mon Sep 17 00:00:00 2001 From: Ftps <63702646+Tps-F@users.noreply.github.com> Date: Fri, 28 Apr 2023 21:43:02 +0900 Subject: [PATCH] Config class (#192) * update config.py * class * class * fix --- config.py | 222 ++++++++++++++++++++----------------------- infer-web.py | 65 ++++++------- vc_infer_pipeline.py | 29 +++--- 3 files changed, 151 insertions(+), 165 deletions(-) diff --git a/config.py b/config.py index 3668e79..4acce95 100644 --- a/config.py +++ b/config.py @@ -1,124 +1,108 @@ -########################硬件参数######################## - -# 填写cuda:x, cpu 或 mps, x指代第几张卡，只支持 N卡 / Apple Silicon 加速 -device = "cuda:0" - -# 9-10-20-30-40系显卡无脑True，不影响质量，>=20显卡开启有加速 -is_half = True - -# 默认0用上所有线程，写数字限制CPU资源使用 -n_cpu = 0 - -########################硬件参数######################## - - -##################下为参数处理逻辑，勿动################## - -########################命令行参数######################## import argparse - -parser = argparse.ArgumentParser() -parser.add_argument("--port", type=int, default=7865, help="Listen port") -parser.add_argument("--pycmd", type=str, default="python", help="Python command") -parser.add_argument("--colab", action="store_true", help="Launch in colab") -parser.add_argument( - "--noparallel", action="store_true", help="Disable parallel processing" -) -parser.add_argument( - "--noautoopen", action="store_true", help="Do not open in browser automatically" -) -cmd_opts = parser.parse_args() - -python_cmd = cmd_opts.pycmd -listen_port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865 -iscolab = cmd_opts.colab -noparallel = cmd_opts.noparallel -noautoopen = cmd_opts.noautoopen -########################命令行参数######################## - +import glob import sys import torch - - -# has_mps is only available in nightly pytorch (for now) and MasOS 12.3+. -# check `getattr` and try it for compatibility -def has_mps() -> bool: - if sys.platform != "darwin": - return False - else: - if not getattr(torch, "has_mps", False): - return False - try: - torch.zeros(1).to(torch.device("mps")) - return True - except Exception: - return False - - -if not torch.cuda.is_available(): - if has_mps(): - print("没有发现支持的N卡, 使用MPS进行推理") - device = "mps" - else: - print("没有发现支持的N卡, 使用CPU进行推理") - device = "cpu" - is_half = False - -gpu_mem = None -if device not in ["cpu", "mps"]: - i_device = int(device.split(":")[-1]) - gpu_name = torch.cuda.get_device_name(i_device) - if ( - "16" in gpu_name - or "P40" in gpu_name.upper() - or "1070" in gpu_name - or "1080" in gpu_name - ): - print("16系显卡强制单精度") - is_half = False - with open("configs/32k.json", "r") as f: - strr = f.read().replace("true", "false") - with open("configs/32k.json", "w") as f: - f.write(strr) - with open("configs/40k.json", "r") as f: - strr = f.read().replace("true", "false") - with open("configs/40k.json", "w") as f: - f.write(strr) - with open("configs/48k.json", "r") as f: - strr = f.read().replace("true", "false") - with open("configs/48k.json", "w") as f: - f.write(strr) - with open("trainset_preprocess_pipeline_print.py", "r") as f: - strr = f.read().replace("3.7", "3.0") - with open("trainset_preprocess_pipeline_print.py", "w") as f: - f.write(strr) - gpu_mem = int( - torch.cuda.get_device_properties(i_device).total_memory / 1024 / 1024 / 1024 - + 0.4 - ) - if gpu_mem <= 4: - with open("trainset_preprocess_pipeline_print.py", "r") as f: - strr = f.read().replace("3.7", "3.0") - with open("trainset_preprocess_pipeline_print.py", "w") as f: - f.write(strr) from multiprocessing import cpu_count -if n_cpu == 0: - n_cpu = cpu_count() -if is_half: - # 6G显存配置 - x_pad = 3 - x_query = 10 - x_center = 60 - x_max = 65 -else: - # 5G显存配置 - x_pad = 1 - x_query = 6 - x_center = 38 - x_max = 41 -if gpu_mem != None and gpu_mem <= 4: - x_pad = 1 - x_query = 5 - x_center = 30 - x_max = 32 + +class Config: + def __init__(self): + self.device = "cuda:0" + self.is_half = True + self.n_cpu = 0 + self.gpu_name = None + self.gpu_mem = None + ( + self.python_cmd, + self.listen_port, + self.iscolab, + self.noparallel, + self.noautoopen, + ) = self.arg_parse() + self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config() + + def arg_parse(self) -> tuple: + parser = argparse.ArgumentParser() + parser.add_argument("--port", type=int, default=7865, help="Listen port") + parser.add_argument( + "--pycmd", type=str, default="python", help="Python command" + ) + parser.add_argument("--colab", action="store_true", help="Launch in colab") + parser.add_argument( + "--noparallel", action="store_true", help="Disable parallel processing" + ) + parser.add_argument( + "--noautoopen", + action="store_true", + help="Do not open in browser automatically", + ) + cmd_opts = parser.parse_args() + + cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865 + + return ( + cmd_opts.pycmd, + cmd_opts.port, + cmd_opts.colab, + cmd_opts.noparallel, + cmd_opts.noautoopen, + ) + + def device_config(self) -> tuple: + if torch.cuda.is_available(): + self.gpu_name = torch.cuda.get_device_name(int(self.device.split(":")[-1])) + i_device = int(self.device.split(":")[-1]) + self.gpu_name = torch.cuda.get_device_name(i_device) + if ( + "16" in self.gpu_name + or "P40" in self.gpu_name.upper() + or "1070" in self.gpu_name + or "1080" in self.gpu_name + ): + print("16系显卡强制单精度") + self.is_half = False + for config_file in ["32k.json", "40k.json", "48k.json"]: + with open(f"configs/{config_file}", "a") as f: + strr = f.read().replace("true", "false") + f.write(strr) + self.gpu_mem = int( + torch.cuda.get_device_properties(i_device).total_memory + / 1024 + / 1024 + / 1024 + + 0.4 + ) + if self.gpu_mem <= 4: + with open("trainset_preprocess_pipeline_print.py", "a") as f: + strr = f.read().replace("3.7", "3.0") + f.write(strr) + elif torch.backends.mps.is_available(): + print("没有发现支持的N卡, 使用MPS进行推理") + self.device = "mps" + else: + print("没有发现支持的N卡, 使用CPU进行推理") + self.device = "cpu" + + if self.n_cpu == 0: + self.n_cpu = cpu_count() + + if self.is_half: + # 6G显存配置 + x_pad = 3 + x_query = 10 + x_center = 60 + x_max = 65 + else: + # 5G显存配置 + x_pad = 1 + x_query = 6 + x_center = 38 + x_max = 41 + + if self.gpu_name != None and self.gpu_mem <= 4: + x_pad = 1 + x_query = 5 + x_center = 30 + x_max = 32 + + return x_pad, x_query, x_center, x_max diff --git a/infer-web.py b/infer-web.py index 7975c6f..863b0b0 100644 --- a/infer-web.py +++ b/infer-web.py @@ -74,19 +74,12 @@ from fairseq import checkpoint_utils import gradio as gr import logging from vc_infer_pipeline import VC -from config import ( - is_half, - device, - python_cmd, - listen_port, - iscolab, - noparallel, - noautoopen, -) +from config import Config from infer_uvr5 import _audio_pre_ from my_utils import load_audio from train.process_ckpt import show_info, change_info, merge, extract_small_model +config = Config() # from trainset_preprocess_pipeline import PreProcess logging.getLogger("numba").setLevel(logging.WARNING) @@ -111,8 +104,8 @@ def load_hubert(): suffix="", ) hubert_model = models[0] - hubert_model = hubert_model.to(device) - if is_half: + hubert_model = hubert_model.to(config.device) + if config.is_half: hubert_model = hubert_model.half() else: hubert_model = hubert_model.float() @@ -259,8 +252,8 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg): pre_fun = _audio_pre_( agg=int(agg), model_path=os.path.join(weight_uvr5_root, model_name + ".pth"), - device=device, - is_half=is_half, + device=config.device, + is_half=config.is_half, ) if inp_root != "": paths = [os.path.join(inp_root, name) for name in os.listdir(inp_root)] @@ -328,7 +321,9 @@ def get_vc(sid): ###楼下不这么折腾清理不干净 if_f0 = cpt.get("f0", 1) if if_f0 == 1: - net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=is_half) + net_g = SynthesizerTrnMs256NSFsid( + *cpt["config"], is_half=config.is_half + ) else: net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"]) del net_g, cpt @@ -343,17 +338,17 @@ def get_vc(sid): cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] # n_spk if_f0 = cpt.get("f0", 1) if if_f0 == 1: - net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=is_half) + net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half) else: net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"]) del net_g.enc_q print(net_g.load_state_dict(cpt["weight"], strict=False)) # 不加这一行清不干净, 真奇葩 - net_g.eval().to(device) - if is_half: + net_g.eval().to(config.device) + if config.is_half: net_g = net_g.half() else: net_g = net_g.float() - vc = VC(tgt_sr, device, is_half) + vc = VC(tgt_sr, config) n_spk = cpt["config"][-3] return {"visible": True, "maximum": n_spk, "__type__": "update"} @@ -423,10 +418,10 @@ def preprocess_dataset(trainset_dir, exp_dir, sr, n_p=ncpu): f = open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "w") f.close() cmd = ( - python_cmd + config.python_cmd + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s " % (trainset_dir, sr, n_p, now_dir, exp_dir) - + str(noparallel) + + str(config.noparallel) ) print(cmd) p = Popen(cmd, shell=True) # , stdin=PIPE, stdout=PIPE,stderr=PIPE,cwd=now_dir @@ -458,7 +453,7 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir): f = open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "w") f.close() if if_f0 == "是": - cmd = python_cmd + " extract_f0_print.py %s/logs/%s %s %s" % ( + cmd = config.python_cmd + " extract_f0_print.py %s/logs/%s %s %s" % ( now_dir, exp_dir, n_p, @@ -498,8 +493,8 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir): leng = len(gpus) ps = [] for idx, n_g in enumerate(gpus): - cmd = python_cmd + " extract_feature_print.py %s %s %s %s %s/logs/%s" % ( - device, + cmd = config.python_cmd + " extract_feature_print.py %s %s %s %s %s/logs/%s" % ( + config.device, leng, idx, n_g, @@ -621,7 +616,7 @@ def click_train( print("use gpus:", gpus16) if gpus16: cmd = ( - python_cmd + config.python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % ( exp_dir1, @@ -639,7 +634,7 @@ def click_train( ) else: cmd = ( - python_cmd + config.python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % ( exp_dir1, @@ -736,10 +731,10 @@ def train1key( #########step1:处理数据 open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir1), "w").close() cmd = ( - python_cmd + config.python_cmd + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s " % (trainset_dir4, sr_dict[sr2], ncpu, now_dir, exp_dir1) - + str(noparallel) + + str(config.noparallel) ) yield get_info_str("step1:正在处理数据") yield get_info_str(cmd) @@ -751,7 +746,7 @@ def train1key( open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir1), "w") if if_f0_3 == "是": yield get_info_str("step2a:正在提取音高") - cmd = python_cmd + " extract_f0_print.py %s/logs/%s %s %s" % ( + cmd = config.python_cmd + " extract_f0_print.py %s/logs/%s %s %s" % ( now_dir, exp_dir1, np7, @@ -770,8 +765,8 @@ def train1key( leng = len(gpus) ps = [] for idx, n_g in enumerate(gpus): - cmd = python_cmd + " extract_feature_print.py %s %s %s %s %s/logs/%s" % ( - device, + cmd = config.python_cmd + " extract_feature_print.py %s %s %s %s %s/logs/%s" % ( + config.device, leng, idx, n_g, @@ -852,7 +847,7 @@ def train1key( yield get_info_str("write filelist done") if gpus16: cmd = ( - python_cmd + config.python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % ( exp_dir1, @@ -870,7 +865,7 @@ def train1key( ) else: cmd = ( - python_cmd + config.python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % ( exp_dir1, @@ -1531,12 +1526,12 @@ with gr.Blocks() as app: # with gr.TabItem(i18n("点击查看交流、问题反馈群号")): # gr.Markdown(value=i18n("xxxxx")) - if iscolab: + if config.iscolab: app.queue(concurrency_count=511, max_size=1022).launch(share=True) else: app.queue(concurrency_count=511, max_size=1022).launch( server_name="0.0.0.0", - inbrowser=not noautoopen, - server_port=listen_port, + inbrowser=not config.noautoopen, + server_port=config.listen_port, quiet=True, ) diff --git a/vc_infer_pipeline.py b/vc_infer_pipeline.py index 606812f..3f964c7 100644 --- a/vc_infer_pipeline.py +++ b/vc_infer_pipeline.py @@ -1,7 +1,6 @@ import numpy as np, parselmouth, torch, pdb from time import time as ttime import torch.nn.functional as F -from config import x_pad, x_query, x_center, x_max import scipy.signal as signal import pyworld, os, traceback, faiss from scipy import signal @@ -10,17 +9,23 @@ bh, ah = signal.butter(N=5, Wn=48, btype="high", fs=16000) class VC(object): - def __init__(self, tgt_sr, device, is_half): + def __init__(self, tgt_sr, config): + self.x_pad, self.x_query, self.x_center, self.x_max, self.is_half = ( + config.x_pad, + config.x_query, + config.x_center, + config.x_max, + config.is_half + ) self.sr = 16000 # hubert输入采样率 self.window = 160 # 每帧点数 - self.t_pad = self.sr * x_pad # 每条前后pad时间 - self.t_pad_tgt = tgt_sr * x_pad + self.t_pad = self.sr * self.x_pad # 每条前后pad时间 + self.t_pad_tgt = tgt_sr * self.x_pad self.t_pad2 = self.t_pad * 2 - self.t_query = self.sr * x_query # 查询切点前后查询时间 - self.t_center = self.sr * x_center # 查询切点位置 - self.t_max = self.sr * x_max # 免查询时长阈值 - self.device = device - self.is_half = is_half + self.t_query = self.sr * self.x_query # 查询切点前后查询时间 + self.t_center = self.sr * self.x_center # 查询切点位置 + self.t_max = self.sr * self.x_max # 免查询时长阈值 + self.device = config.device def get_f0(self, x, p_len, f0_up_key, f0_method, inp_f0=None): time_step = self.window / self.sr * 1000 @@ -64,8 +69,10 @@ class VC(object): replace_f0 = np.interp( list(range(delta_t)), inp_f0[:, 0] * 100, inp_f0[:, 1] ) - shape = f0[x_pad * tf0 : x_pad * tf0 + len(replace_f0)].shape[0] - f0[x_pad * tf0 : x_pad * tf0 + len(replace_f0)] = replace_f0[:shape] + shape = f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)].shape[0] + f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)] = replace_f0[ + :shape + ] # with open("test_opt.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()])) f0bak = f0.copy() f0_mel = 1127 * np.log(1 + f0 / 700)